2 R paketleri

2.1 Neden paketler var

https://blog.mitchelloharawild.com/blog/user-2018-feature-wall/

2.2 Paketleri nereden bulabiliriz

4 RStudio ile veri yükleme

https://support.rstudio.com/hc/en-us/articles/218611977-Importing-Data-with-RStudio

4.1 Excel

4.2 SPSS

4.3 csv

5 Veriyi görüntüleme

  year          month

Min. :2013 Min. : 1.000
1st Qu.:2013 1st Qu.: 4.000
Median :2013 Median : 7.000
Mean :2013 Mean : 6.549
3rd Qu.:2013 3rd Qu.:10.000
Max. :2013 Max. :12.000

  day           dep_time    sched_dep_time

Min. : 1.00 Min. : 1 Min. : 106
1st Qu.: 8.00 1st Qu.: 907 1st Qu.: 906
Median :16.00 Median :1401 Median :1359
Mean :15.71 Mean :1349 Mean :1344
3rd Qu.:23.00 3rd Qu.:1744 3rd Qu.:1729
Max. :31.00 Max. :2400 Max. :2359
NA’s :8255
dep_delay arr_time
Min. : -43.00 Min. : 1
1st Qu.: -5.00 1st Qu.:1104
Median : -2.00 Median :1535
Mean : 12.64 Mean :1502
3rd Qu.: 11.00 3rd Qu.:1940
Max. :1301.00 Max. :2400
NA’s :8255 NA’s :8713
sched_arr_time arr_delay
Min. : 1 Min. : -86.000
1st Qu.:1124 1st Qu.: -17.000
Median :1556 Median : -5.000
Mean :1536 Mean : 6.895
3rd Qu.:1945 3rd Qu.: 14.000
Max. :2359 Max. :1272.000
NA’s :9430
carrier flight
Length:336776 Min. : 1
Class :character 1st Qu.: 553
Mode :character Median :1496
Mean :1972
3rd Qu.:3465
Max. :8500

tailnum origin
Length:336776 Length:336776
Class :character Class :character
Mode :character Mode :character

 dest              air_time

Length:336776 Min. : 20.0
Class :character 1st Qu.: 82.0
Mode :character Median :129.0
Mean :150.7
3rd Qu.:192.0
Max. :695.0
NA’s :9430
distance hour minute
Min. : 17 Min. : 1.00 Min. : 0.00
1st Qu.: 502 1st Qu.: 9.00 1st Qu.: 8.00
Median : 872 Median :13.00 Median :29.00
Mean :1040 Mean :13.18 Mean :26.23
3rd Qu.:1389 3rd Qu.:17.00 3rd Qu.:44.00
Max. :4983 Max. :23.00 Max. :59.00

time_hour
Min. :2013-01-01 05:00:00
1st Qu.:2013-04-04 13:00:00
Median :2013-07-03 10:00:00
Mean :2013-07-03 05:22:54
3rd Qu.:2013-10-01 07:00:00
Max. :2013-12-31 23:00:00

6 Veriyi değiştirme

6.1 Veriyi kod ile değiştirelim

6.2 Veriyi eklentilerle değiştirme

6.3 RStudio aracılığıyla recode

questionr paketi kullanılacak

https://juba.github.io/questionr/articles/recoding_addins.html

7 Basit tanımlayıcı istatistikler

summary()

mean

median

min

max

sd

table()

Parsed with column specification: cols( Sepal.Length = col_double(), Sepal.Width = col_double(), Petal.Length = col_double(), Petal.Width = col_double(), Species = col_character() )

DESCRIPTIVES

Descriptives
───────────────────────────────────────────────────── Species Sepal.Length
───────────────────────────────────────────────────── N setosa 50
versicolor 50
virginica 50
Missing setosa 0
versicolor 0
virginica 0
Mean setosa 5.01
versicolor 5.94
virginica 6.59
Std. error mean setosa 0.0498
versicolor 0.0730
virginica 0.0899
Median setosa 5.00
versicolor 5.90
virginica 6.50
Mode setosa 5.00
versicolor 5.50
virginica 6.30
Sum setosa 250
versicolor 297
virginica 329
Standard deviation setosa 0.352
versicolor 0.516
virginica 0.636
Variance setosa 0.124
versicolor 0.266
virginica 0.404
Range setosa 1.50
versicolor 2.10
virginica 3.00
Minimum setosa 4.30
versicolor 4.90
virginica 4.90
Maximum setosa 5.80
versicolor 7.00
virginica 7.90
Skewness setosa 0.120
versicolor 0.105
virginica 0.118
Std. error skewness setosa 0.337
versicolor 0.337
virginica 0.337
Kurtosis setosa -0.253
versicolor -0.533
virginica 0.0329
Std. error kurtosis setosa 0.662
versicolor 0.662
virginica 0.662
25th percentile setosa 4.80
versicolor 5.60
virginica 6.23
50th percentile setosa 5.00
versicolor 5.90
virginica 6.50
75th percentile setosa 5.20
versicolor 6.30
virginica 6.90
─────────────────────────────────────────────────────

7.1 summarytools

7.1.1 Frequencies

Variable: iris$Species
Type: Factor (unordered)

  Freq % Valid % Valid Cum. % Total % Total Cum.
setosa 50 33.33 33.33 33.33 33.33
versicolor 50 33.33 66.67 33.33 66.67
virginica 50 33.33 100.00 33.33 100.00
<NA> 0 0.00 100.00
Total 150 100.00 100.00 100.00 100.00

8 Rcmdr

  • A Comparative Review of the R Commander GUI for R

http://r4stats.com/articles/software-reviews/r-commander/

9 Sonraki Konular

  • RStudio ile GitHub
  • Hipotez testleri
  • R Markdown ve R Notebook ile tekrarlanabilir rapor

10 Diğer kodlar

11 Geri Bildirim

  1. Bu bir derlemedir, mümkün mertebe alıntılara referans vermeye çalıştım.↩

---
title: R ile analize başlarken^[Bu bir derlemedir, mümkün mertebe alıntılara referans
  vermeye çalıştım.]
author: "Derleyen [Serdar Balcı, MD, Pathologist](https://sbalci.github.io/)"
date: "`r format(Sys.Date())`"
output:
  html_notebook:
    fig_caption: yes
    highlight: kate
    number_sections: yes
    theme: flatly
    toc: yes
    toc_depth: 5
    toc_float: yes
  html_document:
    df_print: paged
    toc: yes
    toc_depth: '5'
---

```{r, include=FALSE}
library(knitr)
opts_chunk$set(comment=NA, prompt=FALSE, cache=FALSE, echo=TRUE, results='asis')
```



# R yükleme

http://www.youtube.com/watch?v=XcBLEVknqvY

[![What is R?](http://img.youtube.com/vi/XcBLEVknqvY/0.jpg)](http://www.youtube.com/watch?v=XcBLEVknqvY)


## R-project

https://cran.r-project.org/

---

[![](https://ismayc.github.io/talks/ness-infer/img/engine.png)](https://ismayc.github.io/talks/ness-infer/slide_deck.html#6)

---

## RStudio

https://www.rstudio.com/

https://www.rstudio.com/products/rstudio/download/

https://moderndive.com/2-getting-started.html

---

### RStudio eklentileri

- Discover and install useful RStudio addins

https://cran.r-project.org/web/packages/addinslist/README.html

https://rstudio.github.io/rstudioaddins/

```{r}
devtools::install_github("rstudio/addinexamples", type = "source")
```


---

## X11

https://www.xquartz.org/

---

## Java OS

https://support.apple.com/kb/dl1572

---

# R paketleri


## Neden paketler var

[![](https://ismayc.github.io/talks/ness-infer/img/appstore.png)](https://ismayc.github.io/talks/ness-infer/slide_deck.html#7)

---

<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script><blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">I love the <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> community.<br>Someone is like, &quot;oh hey peeps, I saw a big need for this mundane but difficult task that I infrequently do, so I created a package that will literally scrape the last bits of peanut butter out of the jar for you. It&#39;s called pbplyr.&quot;<br>What a tribe.</p>&mdash; Frank Elavsky ᴰᵃᵗᵃ ᵂᶦᶻᵃʳᵈ (@Frankly_Data) <a href="https://twitter.com/Frankly_Data/status/1014189095294291968?ref_src=twsrc%5Etfw">July 3, 2018</a></blockquote>

---



https://blog.mitchelloharawild.com/blog/user-2018-feature-wall/

![](https://blog.mitchelloharawild.com/blog/2018-07-11-user-2018-feature-wall_files/final.jpg)

---

## Paketleri nereden bulabiliriz

- Available CRAN Packages By Name
https://cran.r-project.org/web/packages/available_packages_by_name.html

- Bioconductor
https://www.bioconductor.org


---

## R için yardım bulma


```{r yardım}
?mean
??efetch
```



- Vignette

![](figures/vignette.png)

---

- RDocumentation
https://www.rdocumentation.org

- R Package Documentation
https://rdrr.io/

- GitHub

- Stackoverflow

https://stackoverflow.com/

- Google uygun anahtar kelime

![](figures/Google-package-name.png)

---



![](figures/Google-start-with-R.png)

---

- Awesome Cheatsheet
https://github.com/detailyang/awesome-cheatsheet

http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf

https://www.rstudio.com/resources/cheatsheets/


- Awesome R

https://github.com/qinwf/awesome-R#readme

https://awesome-r.com/




- Twitter

https://twitter.com/hashtag/rstats?src=hash


---

## R paket yükleme


```{r paket yükleme}
install.packages("tidyverse", dependencies = TRUE)
install.packages("jmv", dependencies = TRUE)
install.packages("questionr", dependencies = TRUE)
install.packages("Rcmdr", dependencies = TRUE)
install.packages("summarytools")
```


```{r paket çağırma, error=FALSE, message = FALSE, warning = FALSE, eval = TRUE, include = TRUE}
require(tidyverse)
require(jmv)
require(questionr)
library(summarytools)
```

---

# R studio ile proje oluşturma

https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects

![](http://www.rstudio.com/images/docs/projects_new.png)

---

# RStudio ile veri yükleme

https://support.rstudio.com/hc/en-us/articles/218611977-Importing-Data-with-RStudio

![](https://support.rstudio.com/hc/en-us/article_attachments/206277618/data-import-overview.gif)

---

## Excel

## SPSS

## csv


---

# Veriyi görüntüleme

<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script><blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">Spreadsheet users using <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a>:  where&#39;s the data?<a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> users using spreadsheets:  where&#39;s the code?</p>&mdash; Leonard Kiefer (@lenkiefer) <a href="https://twitter.com/lenkiefer/status/1015587475580956672?ref_src=twsrc%5Etfw">July 7, 2018</a></blockquote>



```{r}
library(nycflights13)
summary(flights)
```



```{r}
View(data)
```


```{r}
data
```


```{r}
head
```


```{r}
tail
```


```{r}
glimpse
```


```{r}
str
```


```{r}
skimr::skim()
```

---

# Veriyi değiştirme

## Veriyi kod ile değiştirelim

## Veriyi eklentilerle değiştirme

![](figures/change_data.png)

---


## RStudio aracılığıyla recode

*questionr* paketi kullanılacak

![](figures/level_recode.png)

---



https://juba.github.io/questionr/articles/recoding_addins.html


![](https://raw.githubusercontent.com/juba/questionr/master/resources/screenshots/irec_1.png)


---

![](https://raw.githubusercontent.com/juba/questionr/master/resources/screenshots/irec_2.png)


---

![](https://raw.githubusercontent.com/juba/questionr/master/resources/screenshots/irec_3.png)


---

# Basit tanımlayıcı istatistikler

summary()

mean

median

min

max

sd

table()



```{r descriptive, echo=TRUE, include = TRUE, fig.show='animate', aniopts='controls'}
library(readr)
irisdata <- read_csv("data/iris.csv")

jmv::descriptives(
    data = irisdata,
    vars = "Sepal.Length",
    splitBy = "Species",
    freq = TRUE,
    hist = TRUE,
    dens = TRUE,
    bar = TRUE,
    box = TRUE,
    violin = TRUE,
    dot = TRUE,
    mode = TRUE,
    sum = TRUE,
    sd = TRUE,
    variance = TRUE,
    range = TRUE,
    se = TRUE,
    skew = TRUE,
    kurt = TRUE,
    quart = TRUE,
    pcEqGr = TRUE)
```

---

```{r scatter, echo=TRUE, include=TRUE}
# install.packages("scatr")

scatr::scat(
    data = irisdata,
    x = "Sepal.Length",
    y = "Sepal.Width",
    group = "Species",
    marg = "dens",
    line = "linear",
    se = TRUE)

```

## summarytools

```{r, include=TRUE}
# library(summarytools)
summarytools::freq(iris$Species, style = "rmarkdown")
```







---

# Rcmdr

```{r}
library(Rcmdr)
```


- A Comparative Review of the R Commander GUI for R

http://r4stats.com/articles/software-reviews/r-commander/


---

# Sonraki Konular

- RStudio ile GitHub
- Hipotez testleri
- R Markdown ve R Notebook ile tekrarlanabilir rapor


---

# Diğer kodlar

- Diğer kodlar için bakınız: [https://sbalci.github.io/](https://sbalci.github.io/)


---

# Geri Bildirim

- Geri bildirim için tıklayınız: _[Geri bildirim formu](https://goo.gl/forms/YjGZ5DHgtPlR1RnB3)_

